Deep Learning – The Future of Successful Businesses

We have come a long way in terms of technology advancement. It is true that we have dreamed, in a more or less romanticized fashion, about artificial intelligence and all we could accomplish through it, however it seems that all our dreams might no longer seem so farfetched.

Over the past several years, new concepts, such as neural networks, deep learning and back propagation have known a steady rise. The world of AI has experienced great change and development, and the discovery of deep learning has caught the eye of worldwide business owners and operators. But what is deep learning and what can it do for the business world?

Deep learning is a branch of artificial intelligence inspired by the structure of the human brain. This technology is like a “thinking computer”, because through its power, machines can gain the ability to intuitively sense the physical world. These machines can learn from and build upon their experience. How does this work?

Through deep learning, a computer can study many examples and then use the acquired “learning” to solve a problem, thus learning to solve by example. This type of learning comes from “hierarchical layers of discovery” in each layer. The computer learns from each layer, and then uses that learning in the next layer to learn more, ‘till the learning is completed through a cumulative learning process in multiple layers.

Given that deep learning technology mimics the human brain, this model has also become known as a neural network, consisting of neurons. Similar to the structure of the human brain, neurons in neural networks are also organized in layers. Deep learning is essentially a process for teaching machines how a thing is done or what a thing is.

In the case of an image, deep learning breaks the image down into a series of hierarchical layers, with each layer unfolding a part of the whole concept. The first layer recognizes edges, the second layer recognizes facial features like an eye or a nose, and the final layer recognizes full faces.

Deep learning in the business world

Surprising or not, the deep learning method can be applied to complex problems and businesses as well. However, in order for it to be practical and achievable in the short term, this method should follow two principles:

A company must have lots of historical data to train the deep learning algorithm;

A company should have a recurring need for predicting things that either: cut costs – for example reducing average handling time in a customer service conversation, or create value, like selling the right product to the right customer at the right time.

These two requirements prove that there are at least a number of uses for the deep learning method. The only questions that a business should answer before employing it are: “What problems need to be solved where deep learning can help?” and “How can such a technology attract new customers?”

Taking into consideration all of the above, it is clear that deep learning can be used in:

Sales – hyper-personalizing email advertisements and sending them only in a specific time slot when the user is statistically most likely to open them and respond positively.

Marketing – bringing order to the overload of marketing data, and providing real-time recommendations for audience targeting, campaign timing and content marketing.

Government Affairs – making them more transparent and preemptively actionable.

Although it might be hard to see it now, but future businesses will mostly rely on data, just like Google, Facebook, Amazon, Netflix and others are doing now. Companies will start creating internal intelligent platforms that will assist humans in labeling data quickly.

What is more, the first companies developing the deep learning operating system will be working on solutions not only for data, but for software and hardware as well.

Although these are still the early days, in the next couple of years, start-ups and established companies will begin releasing commercial solutions for building production-ready deep learning applications. It is only a matter of time until a deep learning operating system will pave the way towards the widespread adoption of practical AI.